cv-site/doc/15-SEO.md

SEO Implementation Guide

Project: CV Interactive Website Last Updated: 2025-11-30 Status: Production Ready

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Overview

This document describes the comprehensive SEO (Search Engine Optimization) implementation for the CV website, including traditional search engine optimization and modern AI-era optimizations for LLM crawlers and AI Overviews.

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SEO Architecture

1. Traditional SEO Elements

Meta Tags (templates/index.html)

<!-- Primary Meta Tags -->
<title>{{.CV.Personal.Name}} - {{.CV.SEO.PageTitle}}</title>
<meta name="title" content="...">
<meta name="description" content="...">
<meta name="keywords" content="...">
<meta name="author" content="...">
<meta name="robots" content="index, follow">
<link rel="canonical" href="{{.CanonicalURL}}">

International SEO (Hreflang)

<link rel="alternate" hreflang="en" href="{{.AlternateEN}}">
<link rel="alternate" hreflang="es" href="{{.AlternateES}}">
<link rel="alternate" hreflang="x-default" href="https://juan.andres.morenorub.io/?lang=en">

Social Media Integration

Platform	Meta Type	Implementation
Facebook	Open Graph	og:type, og:title, og:description, og:image
Twitter/X	Twitter Cards	twitter:card, twitter:title, twitter:description
LinkedIn	Open Graph	Uses same og:* tags

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2. Structured Data (JSON-LD)

The site implements multiple Schema.org types for comprehensive semantic understanding:

Person Schema (Primary)

{
  "@type": "Person",
  "@id": "{{.CV.Personal.Website}}/#person",
  "name": "...",
  "jobTitle": "...",
  "description": "...",
  "knowsAbout": [...],
  "knowsLanguage": [...],
  "worksFor": [...],
  "hasOccupation": [...]
}

Fields included:

• Basic info: name, givenName, familyName, jobTitle
• Contact: email, telephone, url
• Demographics: birthDate, birthPlace, nationality
• Location: address with locality and country
• Social: sameAs (LinkedIn, GitHub, Domestika)
• Education: alumniOf
• Skills: knowsAbout (array of expertise areas)
• Languages: knowsLanguage (with Language type)
• Employment: worksFor (multiple organizations)
• Occupations: hasOccupation (dynamically generated from experience)

WebSite Schema

{
  "@type": "WebSite",
  "name": "... - Professional CV",
  "url": "...",
  "inLanguage": ["en", "es"],
  "potentialAction": { "@type": "SearchAction", ... }
}

BreadcrumbList Schema

{
  "@type": "BreadcrumbList",
  "itemListElement": [
    { "position": 1, "name": "Home", "item": "..." },
    { "position": 2, "name": "CV (English/Español)", "item": ".../?lang=..." }
  ]
}

ProfilePage Schema

{
  "@type": "ProfilePage",
  "mainEntity": { "@id": ".../#person" },
  "dateCreated": "...",
  "dateModified": "...",
  "inLanguage": "..."
}

EducationalOccupationalCredential Schema

Generated dynamically for each education entry:

{
  "@type": "EducationalOccupationalCredential",
  "name": "{{.Degree}}",
  "description": "{{.Field}}",
  "educationalLevel": "Bachelor's Degree",
  "credentialCategory": "degree",
  "recognizedBy": { "@type": "CollegeOrUniversity", ... }
}

Course Schema

Generated dynamically for each course/certification:

{
  "@type": "Course",
  "name": "{{.Title}}",
  "description": "...",
  "provider": { "@type": "Organization", ... },
  "hasCourseInstance": { "@type": "CourseInstance", ... },
  "timeRequired": "{{.Duration}}"
}

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3. AI-Era SEO Optimizations

llms.txt File (static/llms.txt)

A dedicated file for AI crawlers following the llmstxt.org standard:

# llms.txt - AI Crawler Information
name: Juan Andrés Moreno Rubio - Professional CV
description: Interactive curriculum vitae...

## Professional Summary
- Senior Technical Consultant...

## Key Expertise
- SAP Customer Data Cloud...

## Contact
- Website: ...
- LinkedIn: ...

Purpose: Provides AI systems (ChatGPT, Claude, Perplexity, etc.) with structured, human-readable information about the site content.

Plain Text Auto-Detection (/text endpoint)

The site automatically detects text-based browsers and CLI tools, serving a clean 80-character plain text version:

Auto-detected clients:

Client	Type
curl	CLI tool
wget	CLI tool
HTTPie	CLI tool
Lynx	Text browser
w3m	Text browser
Links/ELinks	Text browser
Browsh	Terminal browser
Carbonyl	Terminal browser

Usage:

# Auto-detected (serves plain text):
curl https://juan.andres.morenorub.io/

# Explicit endpoint:
curl https://juan.andres.morenorub.io/text?lang=en

# With Accept header:
curl -H "Accept: text/plain" https://juan.andres.morenorub.io/

Output features:

• 80-character line wrapping
• ASCII art section headers
• Clean, structured text
• All CV content preserved

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robots.txt AI Bot Rules (static/robots.txt)

Explicit permissions for AI crawlers:

Bot	Service	Status
GPTBot	OpenAI/ChatGPT	Allowed
ChatGPT-User	OpenAI	Allowed
ClaudeBot	Anthropic	Allowed
Claude-Web	Anthropic	Allowed
anthropic-ai	Anthropic	Allowed
Google-Extended	Google AI/Gemini	Allowed
PerplexityBot	Perplexity AI	Allowed
cohere-ai	Cohere	Allowed
CCBot	Common Crawl	Allowed
Amazonbot	Amazon/Alexa	Allowed
Applebot	Apple/Siri	Allowed
Copilot	Microsoft	Allowed
YouBot	You.com	Allowed
BraveBot	Brave Search	Allowed

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E-E-A-T Signals

The implementation supports Google's E-E-A-T (Experience, Expertise, Authority, Trust) framework:

Experience

• Detailed work history with responsibilities
• Real project descriptions
• Duration and dates for credibility

Expertise

• Skills categorized by domain
• Technologies listed per job
• Certifications and courses

Authority

• Links to LinkedIn, GitHub, portfolio
• Company associations (SAP, Olympic Broadcasting)
• Client count and project metrics in summary

Trust

• Canonical URLs prevent duplicate content
• HTTPS enforced
• Clear contact information
• Privacy-respecting analytics (Matomo)

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Files Overview

File	Purpose
templates/index.html	Meta tags, JSON-LD schemas
static/robots.txt	Search engine and AI bot directives
static/llms.txt	AI crawler information file
static/sitemap.xml	XML sitemap for search engines
data/cv-en.json	SEO fields (pageTitle, metaTitle, etc.)
data/cv-es.json	Spanish SEO fields
/text endpoint	Plain text CV for CLI/TUI browsers
templates/cv-text.txt	Plain text template

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SEO Data Model

The SEO-specific fields in data/cv-{lang}.json:

{
  "seo": {
    "pageTitle": "Curriculum Vitae",
    "metaTitle": "Professional CV",
    "metaDescription": "18 years of experience in...",
    "ogDescription": "Senior Technical Consultant...",
    "keywords": "CV, Resume, FullStack Developer, SAP CDC..."
  }
}

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Validation & Testing

Schema Validation

Test structured data at:

• Google Rich Results Test
• Schema.org Validator

Expected Schema Count

The site generates 12+ JSON-LD blocks:

• 1 Person schema
• 1 WebSite schema
• 1 BreadcrumbList schema
• 1 ProfilePage schema
• N EducationalOccupationalCredential schemas (1 per education)
• N Course schemas (1 per course)

robots.txt Validation

Test at: Google Robots.txt Tester

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Best Practices Implemented

Content Structure

• Clear H1-H6 heading hierarchy
• Semantic HTML5 elements (article, section, nav)
• Alt text for images
• Descriptive link text

Technical SEO

• Mobile-responsive design
• Fast page load (bundled CSS, preload fonts)
• Canonical URLs
• Hreflang for multilingual
• Sitemap.xml
• robots.txt with AI bot rules

Modern SEO (AI-Era)

• llms.txt file
• Comprehensive JSON-LD schemas
• AI bot permissions in robots.txt
• Clear, parseable content structure

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Maintenance

When to Update

1. Content changes: Update data/cv-{lang}.json SEO fields
2. New sections: Add corresponding Schema.org types
3. New AI bots: Add to robots.txt
4. Annual review: Update llms.txt with current info

Monitoring

• Google Search Console for traditional SEO
• Matomo Analytics for traffic patterns
• Manual testing in AI chat interfaces (ChatGPT, Claude, Perplexity)

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References

• Schema.org
• Google Search Central
• llmstxt.org Standard
• WPBeginner SEO Guide 2025